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wrangle each supported datatype (include use of loaded-in object + filename of saved object):
dataframe
array
text-- use a few different scikit-learn models (train with different built-in and hugging-face corpora) and also show a few hugging-face models. also demo vectorization (scikit-learn) vs. embedding using an already-trained model
image
mixed list of several datatypes
interpolation and imputation
decorators:
list_generalizer, funnel
stacking and unstacking (show examples of how this is useful); also show stack_apply/unstack_apply
io:
loading data (local + remote)
saving data
util:
btwn
dataframe_like, array_like
load_dataframe (show demos with a few different filetypes-- e.g. csv, json, etc. to show how extensions are handled automatically)
core:
show how config.ini is set up and how it can be customized
show how get_default_options and apply_default_options work